eProS—a database and toolbox for investigating protein sequence–structure–function relationships through energy profiles
| Autor: | Florian Heinke, Dirk Labudde, Daniel Stockmann, Stefan Schildbach |
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| Rok vydání: | 2012 |
| Předmět: |
Structure (mathematical logic)
Protein structure database Internet Sequence Database Protein Conformation Proteins Articles Biology computer.software_genre Structure-Activity Relationship Protein sequencing Protein structure Energy profile Genetics Protein function prediction Amino Acid Sequence Databases Protein computer Software Energy (signal processing) |
| Zdroj: | Nucleic Acids Research |
| ISSN: | 1362-4962 0305-1048 |
| Popis: | Gaining information about structural and functional features of newly identified proteins is often a difficult task. This information is crucial for understanding sequence-structure-function relationships of target proteins and, thus, essential in comprehending the mechanisms and dynamics of the molecular systems of interest. Using protein energy profiles is a novel approach that can contribute in addressing such problems. An energy profile corresponds to the sequence of energy values that are derived from a coarse-grained energy model. Energy profiles can be computed from protein structures or predicted from sequences. As shown, correspondences and dissimilarities in energy profiles can be applied for investigations of protein mechanics and dynamics. We developed eProS (energy profile suite, freely available at http://bioservices.hs-mittweida.de/Epros/), a database that provides ∼76 000 pre-calculated energy profiles as well as a toolbox for addressing numerous problems of structure biology. Energy profiles can be browsed, visualized, calculated from an uploaded structure or predicted from sequence. Furthermore, it is possible to align energy profiles of interest or compare them with all entries in the eProS database to identify significantly similar energy profiles and, thus, possibly relevant structural and functional relationships. Additionally, annotations and cross-links from numerous sources provide a broad view of potential biological correspondences. |
| Databáze: | OpenAIRE |
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